Two Sides of the Same Coin? Neutral Monism as an Attempt to Reconcile Subjectivity and Objectivity in Personal Identity
Bibliographic record
Abstract
Abstract Standard views of personal identity over time often hover uneasily between the subjective, first-person dimension (e. g. psychological continuity), and the objective, third-person dimension (e. g. biological continuity) of a person’s life. Since both dimensions capture something integral to personal identity, we show that neither can successfully be discarded in favor of the other. The apparent need to reconcile subjectivity and objectivity, however, presents standard views with problems both in seeking an ontological footing of, as well as epistemic evidence for, personal identity. We contend that a fresh look at neutral monism offers a novel way to tackle these problems; counting on the most fundamental building blocks of reality to be ontologically neutral with regards to subjectivity and objectivity of personal identity. If the basic units of reality are, in fact, ontologically neutral – but can give rise to mental as well as physical events – these basic units of reality might account for both subjectivity and objectivity in personal identity. If this were true, it would turn out that subjectivity and objectivity are not conflictive dimensions of personal identity but rather two sides of the same coin.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.059 |
| Scholarly communication | 0.010 | 0.021 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".